Batteries have been used in automotive and industrial applications for many years. Accurate estimation of the amount of energy in a battery (hereinafter referred to as the state-of-charge or SOC) is very useful. It allows a battery management system to maximize battery performance, reliability and lifetime. It also allows for more accurate range and power output prediction for electric or hybrid vehicles.
Existing techniques for determining SOC often use the battery open-circuit voltage (OCV) to estimate SOC, using a table of previously determined values that relate OCV to SOC. One limitation of this approach is that OCV is normally measured when the battery is in a “relaxed state”, meaning that the measured voltage across the battery terminals has stopped changing after the current flow has stopped. Depending on various operational parameters, reaching a relaxed state can take a considerable period of time. Techniques for predicting OCV from measured voltages have been proposed that use the following formula:V(t)=OCV−αe−t/τ
where V(t) is a voltage measurement taken at time t, α is the overpotential and τ is the time constant. These techniques use a pre-characterized value for τ and statistical mathematical techniques to obtain α and OCV from a set of voltages measurements taken over an idle period in which negligible power is drawn from the battery. Thus a value for OCV, and hence SOC, is obtained without waiting until the battery is fully in a “relaxed state” and the measured battery voltages have stabilized. Unfortunately, the foregoing approach may still yield inaccurate values of OCV and also may require excessive idle periods in which to collect voltage measurements.